Linked Life Data

12876725

Source:http://linkedlifedata.com/resource/pubmed/id/12876725

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2003-7-23
pubmed:abstractText
The large line-width associated with electron paramagnetic resonance imaging (EPRI) requires effective algorithms to deconvolve the true spatial profiles of spins from the measured projection data. The commonly used Fourier transform (FT) deconvolution algorithm is easy to implement but suffers from the division-by-zero problem. As a result, a couple of parameters are used to control the deconvolution performance. However, this is inconvenient and the deconvolution results are subject to the experience of the operators. In the present work we examined FT deconvolution for EPRI, and proposed an automatic algorithm to determine the cutoff frequency by calculating the piecewise variance of the division result of the Fourier amplitude spectra. The deconvolution algorithm and the filtered back-projection image reconstruction algorithm were implemented and validated using 3D phantom and in vivo imaging data. It was clearly observed that the image resolution improved after deconvolution with the proposed algorithm.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0740-3194
pubmed:author
pubmed:copyrightInfo
Copyright 2003 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:volume
50
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
444-8
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Deconvolution algorithm based on automatic cutoff frequency selection for EPR imaging.
pubmed:affiliation
Center for Biomedical EPR Spectroscopy and Imaging, Davis Heart and Lung Research Institute, Ohio State University College of Medicine, Columbus, Ohio 43210, USA.
pubmed:publicationType
Journal Article